Affiliation:
1. Sir Syed University of Engineering and Technology, Pakistan
Abstract
There is a lack of reliable economical methods for forecasting house prices for those who wish to buy a house according to their living standards. This paper presents details of predictive analytics for house pricing in three different towns of Karachi, Pakistan according to different living standards based on machine learning (ML) methods. The purpose of this study is to determine which data set features contribute greatly to the accuracy of the predictions when experimenting with selected predictive techniques. The house price value has been analysed using five different ML methods. A model selection has been made by comparing the accuracy of the techniques based on some performance metrics and the best technique was used to predict the house price value.
Publisher
NED University of Engineering and Technology
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